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All Journal Jurnal Ekonomi ASAS : Jurnal Hukum Ekonomi Syariah Agrointek Jurnal Akuntansi Multiparadigma Jurnal Teknologi Informasi dan Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Resona : Jurnal Ilmiah Pengabdian Masyarakat Jurnal Pilar Nusa Mandiri Smart Medical Journal Al-Urban: Jurnal Ekonomi Syariah dan Filantropi Islam Jurnal Teknik Informatika STMIK Antar Bangsa IKRA-ITH Informatika : Jurnal Komputer dan Informatika Expose: Jurnal Ilmu Komunikasi Distribusi FIDUSIA : JURNAL KEUANGAN DAN PERBANKAN Journal of Saintech Transfer Ad-Deenar: Jurnal Ekonomi dan Bisnis Islam JURNAL TEKNOLOGI INFORMASI Jurnal Ilmu Komputer dan Bisnis Jurnal Teknologi Informasi dan Terapan (J-TIT) El-Usrah: Jurnal Hukum Keluarga Jurnal Ilmiah Edunomika (JIE) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Manajemen dan Bisnis Kreatif Al-Mal:Jurnal Akuntansi dan Keuangan Islam Journal of Islamic Law Jurnal AbdiMas Nusa Mandiri JOURNAL LA MEDIHEALTICO Jurnal Abdimas Bina Bangsa Abditeknika - Jurnal Pengabdian Kepada Masyarakat Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen ProBisnis : Jurnal Manajemen Jurnal Pengabdian pada Masyarakat Ilmu Pengetahuan dan Teknologi Terintegrasi Paradigma INOVASI: Jurnal Hasil Pengabdian Masyarakat Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) International Journal of Economics (IJEC) Indonesian Journal of Islamic Economics and Finance Seminar Nasional Hasil Penelitian LP2M UNM ABDIMU Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Jurnal Penelitian dan Pengabdian Masyarakat IIJSE Majapahit Journal of Islamic Finance dan Management Majapahit Journal of Islamic Finance dan Management Jurnal Manajemen Rekayasa (Journal of Engineering Management) Engagement: Jurnal Pengabdian Kepada Masyarakat SMART: Jurnal Pengabdian Kepada Masyarakat Al-Intaj : Jurnal Ekonomi dan Perbankan Syariah Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Electrical Engineering and Informatics Jurnal of Islamic Economic Studies Smart Humanity: Jurnal Pengabdian Masyarakat Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal)
Ridwansyah Ridwansyah
Program Studi Ilmu dan Teknologi Pangan Fakultas Pertanian USU Medan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Optimizing Heart Failure Detection: A Comparison between Naive Bayes and Particle Swarm Optimization Hamid, Abdul; Ridwansyah, Ridwansyah
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3284

Abstract

This research focuses on the importance of early detection of heart failure which is a serious global health problem. Given the variety of symptoms of heart failure, accurate early detection methods are needed with the aim of reducing the impact of this disease. This study uses the Naïve Bayes (NB) method which has been proven effective in classifying heart failure with significant variations in accuracy by integrating Particle Swarm Optimization (PSO) to improve the model. The evaluation model involves a confusion matrix including accuracy, precision, recall, and Area Under the Curve. The research results show that the integration of PSO in NB results in an increase in accuracy of 7.73%, an increase in precision of 6.42%, and an increase in recall of 1.93%. Although there was a small decrease in AUC. This research shows that the success of NB with PSO can help improve the performance of early detection of heart failure. This indicates the importance of this research in developing more accurate and effective detection methods for critical health conditions such as heart failure.
Optimizing Heart Failure Detection: A Comparison between Naive Bayes and Particle Swarm Optimization Hamid, Abdul; Ridwansyah, Ridwansyah
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3284

Abstract

This research focuses on the importance of early detection of heart failure which is a serious global health problem. Given the variety of symptoms of heart failure, accurate early detection methods are needed with the aim of reducing the impact of this disease. This study uses the Naïve Bayes (NB) method which has been proven effective in classifying heart failure with significant variations in accuracy by integrating Particle Swarm Optimization (PSO) to improve the model. The evaluation model involves a confusion matrix including accuracy, precision, recall, and Area Under the Curve. The research results show that the integration of PSO in NB results in an increase in accuracy of 7.73%, an increase in precision of 6.42%, and an increase in recall of 1.93%. Although there was a small decrease in AUC. This research shows that the success of NB with PSO can help improve the performance of early detection of heart failure. This indicates the importance of this research in developing more accurate and effective detection methods for critical health conditions such as heart failure.
KLASIFIKASI ANAK BERKEBUTUHAN KHUSUS TUNAGRAHITA MENGGUNAKAN METODE ALGORITMA C4.5 Priyatama, I Made Dananjaya; Ridwansyah, Ridwansyah
Paradigma - Jurnal Komputer dan Informatika Vol. 24 No. 1 (2022): Periode Maret 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/paradigma.v24i1.1087

Abstract

Children with mental retardation are children who have differences from other children that can be seen significantly with our naked eyes, because they are children with special needs both mentally, physically and can be seen from their psychology. Intellectuals of mentally retarded children are socially slower to do everything in achieving the goals they want optimally. Children with mental retardation usually have disorders such as speech disorders or physical and mental disabilities, as well as uncontrollable emotions. The problems that exist with teachers of children with special needs are because many teachers do not know the characteristics of mentally retarded children and how to handle them through IQ levels and several other factors. In solving problems for children with special needs, these children need to be classified due to their differences from one person to another in developmental delays and physical conditions they experience, so it is necessary to distinguish educational or teaching strategies that are designed and programmed for them. With the C4.5 algorithm method, which can classify children with special needs based on existing characteristics with data that is tested with a model that is used cross validation and evaluated with a confusion matrix. Based on the results of testing with this method, the accuracy obtained is very high so that it can be used by teaching staff from the accurate information.
Grouping Data in Predicting Infant Mortality Using K-Means and Decision Tree Ridwansyah, Ridwansyah; Riyanto, Verry; Hamid, Abdul; Rahayu, Sri; Purnama, Jajang Jaya
Paradigma - Jurnal Komputer dan Informatika Vol. 24 No. 2 (2022): September 2022 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/paradigma.v24i2.1399

Abstract

Death is something that we cannot avoid where, when and how death comes. The high infant mortality rate is the main thing and the Indonesian government must prioritize, one of the government's efforts to reduce infant mortality is by conducting a surveillance program, namely PWS KIA where the program is uniting the health of mothers and babies in the local area, basically there are several infant deaths that have causes from the time of pregnancy, accidents, disasters, diseases or because it is destiny from God, for that research is carried out in classifying infant mortality data. For grouping infant mortality data, a K-Means method is needed to analyze data by carrying out a data modeling process without supervision or also known as unsupervised learning. In showing the centroid in the early stages of the k-means algorithm, it is very influential on the results of the cluster carried out on the infant mortality dataset. taken from data.go.id with different centroid results. The results of the clustering model pattern that can be trusted by the government or the Health department to prevent infant mortality. From the clustering results, four labels are tested again using the decision tree algorithm.
Optimization of the YOLOv7 Object Detection Algorithm for Estimating the Amount of Apple Harvest Riyanto, Verry; Nawawi, Imam; Ridwansyah, Ridwansyah; Wijaya, Ganda; Haryanto, Toto
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 1 (2023): March 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i1.1809

Abstract

The increasing population consumed in high production and food needs for survival. Apples are one of the crop harvest products in Indonesia whose needs are increasing, because they are not only needed for human vitamins but can be used as hand fruit or a form of gratitude to those who receive the fruit. In the process of harvesting apples in agricultural land, harvesting is often found which is not feasible in the hands of consumers because it takes too long for apples to not be harvested when the condition of the fruit is feasible in maturity. Therefore, the authors approach this problem by processing the image results obtained to form a detection model, whether the apples are said to be feasible to be harvested immediately and from the image results it can also be calculated the number of fruits captured by the image model , feature enhancements Estimates on objects from this image model are expected to provide more timely harvest predictions in order to provide longer aging of apples and good fruit quality after reaching consumers
The Method User Experience Questionnaire Analysis of Identitas Kependudukan Digital Application Farlian, Galang Fachrul; Ridwansyah, Ridwansyah
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 2 (2023): September 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i2.2353

Abstract

User Experience (UX) becomes important to explore and fulfill the needs for developing user-focused applications or products. The problems that exist to measure the level of user experience in the Digital Resident Identity (IKD) application and complaints submitted by users tend to lead to system and service quality problems in the IKD application. Then research purposes are assessed to evaluate the extent to which users can utilize and interact with the application. The method used by researchers is the User Experience Questionnaire (UEQ). UEQ is a widely used scoring methodology used to quantitatively measure user experience by administering a questionnaire to individuals that measures their subjective experiences and perceptions. Variables in UEQ, namely: efficiency, perspicuity, dependability, novelty, stimulation, and interestingness. The evaluation results of user experience in IKD applications using UEQ showed that there were 5 variables that received positive evaluation results, including attractiveness variables (mean 2.14), clarity variables (perspicuity) (mean 1.725), efficiency variables (efficiency) ( mean 1.725), accuracy variable (mean 1.525), and stimulation variable (mean 1.475). Whereas the novelty variable (mean 0.602) gets neutral evaluation results. From these results it can be used by IKD application developers to improve the user experience (user experience) of IKD applications on novelty variables by improving the appearance of applications that are more creative, inventive, and also cutting edge. The developer can pay attention to the recommendations that have been presented in this study. Parties who wish to conduct further research can use other evaluation methods such as Heuristic Evaluation.
Co-Authors Abdul Hamid Adris Ade Putra Ahmad Mujahid, Ahmad Alayzha, Vivi Nur Alfian, Achmad Ali, Karnila Allimmah, Khoirunnisa Nurul Amelia, Merry Amrina, Dania Hellin Andi Saryoko ANGGUN RACHMAWATI, ANGGUN Anip Dwi Saputro, Anip Dwi Anus Wuryanto Ardini Saptaningsih Raksanagara, Ardini Saptaningsih Arisca, Nurmalita Asep Wasid Asnawati Asnawati Ayasar, Prayogi Putra Bahar, Muh. Mahdinul Baharuddin, Andi Rakhmat Debi Irawan Dinda Fali Rifan Djawad , Yasser Abd Elisa Julianti Era Yusraini Erike Anggraeni Ersi Sisdianto Esty Purwaningsih Evendi, Rustam Faika, Siti Faizah, Siti FARAH FAHMA Farhana, Nur Laila Farlian, Galang Fachrul Fatma Lestari Fortuna, Salsabila Mutia Fortuna, Salsabilla Mutia Ganda Wijaya, Ganda Ganggang Canggi Arnanto Gianova, Erin Gusti, Wahyu Ramadhani Gustika Nurmalia Hafis Nurdin Haripuddin . Haris Herdiansyah, Haris Hendra Jaya Heni Noviarita Herfina, Inne Dwi Herlambang, Saifuddin Herliawan, Irwan Idris, Maruf Idris, Ma’ruf Ifna, Nur Ifna Imam Nawawi, Imam Indah Ariyati Indayani Indra Sukma, Indra Irfansyah, Nanda Irmawati Carolina Ispandi Ispandi, Ispandi Jajang Jaya Purnama Jhody Wiraputra Juwita, Safna Kahfi, Ahmad Hafidzul Khaswar Syamsu Kresna Ramanda Labusab, Labusab Lasmiatun, KMT Latifah Latifah Lawelendo, Lawelendo Mantasia Mantasia Marariza, Helma Mayzal, Tiondon Meilissa Ayu Pratiwi Mia Selvina Moh. Muslih Monalysa, Lita Muhammad Iqbal Fasa Mustamin Mustamin Mutahharah Hasyim, Mutahharah Naffati, Abdel Kadir Nawawi, Hendri Mahmud Northa Idaman Nugraha, Fitra Septia Nurhasmi Nurhasmi Nursalma, Intan Nusasenjaya, Radite Okta Sari Okta Supriyaningsih Oky Kurniawan Pariabti Palloan Pariury, Phenny Ponta, Tasri Pratama, Reza Hardian Priyatama, I Made Dananjaya Purnama Soiswaty, Dwi Purwadhi Purwadhi Purwoko, Reza Yuridian Ramadhani, Mutiara Ramdani, Nico Razimi, Mohd Syahril Ahmad Resti Lia Andharsaputri Retno Sari Rian Andriani, Rian Rima Melati Risal, Ahmad Risnandar, Risnandar Rizki, Marisa Rizkyansyah, Muhamad RIZQINA, AULIA LAILY Rosyda, Susy Ruray, Titiek Arafiani Sabril, Aulia Samad, Putri IS Samman, Muhammad Sanusi, Dirga Kaso Sari, Defya Sari, Yetri Martika Sari, Yuniar Sartika Setiawan, Zunan Siti Munawaroh Sopiyan, Riyan SRI RAHAYU suhaeb, Sutarsi Suhartono sulis, sulistiawaty sulis, sulistiawaty - Supriadi Supriadi Suprianingsih, Okta Susanto, Is Susy Rosyida Tauhidin Abas, Totoh Terip Karo-Karo Theresia Santi, Theresia Titi Candra Sunarti Toto Haryanto Tubarad, Chara Pratami Tidespania Tyas, Prayoga Ning Usman Usman Verry Riyanto Wahrini, Retyana Wahyu Iryana Weny Rosilawati Wiraputra, Jhody Yahya, Haidar Silmi Yunita Sari